我想绘制连续变量和分类变量(geom_boxplot
和ggplot2
)之间的关系的箱线图,这在几种情况下(facet_wrap
)。很简单:
data("CO2")
ggplot(CO2, aes(Treatment, uptake) ) +
geom_boxplot(aes(Treatment, uptake),
col="black", fill="white", alpha=0, width=.5) +
geom_point(col="black", size=1.2) +
facet_wrap(~Type, ncol=3, nrow=6, scales= "free_y") +
theme_bw() +
ylab("Uptake")
结果:
这个玩具数据集非常不错,但是应用于我自己的数据(facet_wrap使我能够绘制18个不同的图)y轴几乎不可读,其y标记的数量不同并且它们之间的间距也不同:
协调y轴的最佳方法是什么? (即,无论是什么中断,y轴刻度之间的间距都是相等的-由于我的连续变量的变化范围变化很大,因此这些位置必定会从一个图变为另一个图
非常感谢您的帮助:)
最佳答案
通过在y轴值上应用pretty()
并扩展第一个值/最后一个值,可以手动扩展每个构面的值,从而可以将每个构面的限制强制为相对漂亮的外观。
以下是使用Diamonds数据集的示例:
# normal facet_wrap plot with many different y-axis scales across facets
p <- ggplot(diamonds %>% filter(cut %in% c("Fair", "Ideal")),
aes(x = cut, y = carat) ) +
geom_boxplot(col="black", fill="white", alpha=0, width=.5) +
geom_point(col="black", size=1.2) +
facet_wrap(~clarity, scales= "free_y", nrow = 2) +
theme_bw() +
ylab("Uptake")
p
# modified plot with consistent label placements
p +
# Manually create values to expand the scale, by finding "pretty"
# values that are slightly larger than the range of y-axis values
# within each facet; set alpha = 0 since they aren't meant to be seen
geom_point(data = . %>%
group_by(clarity) %>% #group by facet variable
summarise(y.min = pretty(carat)[1],
y.max = pretty(carat)[length(pretty(carat))]) %>%
tidyr::gather(key, value, -clarity),
aes(x = 1, y = value),
inherit.aes = FALSE, alpha = 0) +
# Turn off automatical scale expansion, & manually set scale breaks
# as an evenly spaced sequence (with the "pretty" values created above
# providing the limits for each facet). If there are many facets to
# show, I recommend no more than 3 labels in each facet, to keep things
# simple.
scale_y_continuous(breaks = function(x) seq(from = x[1],
to = x[2],
length.out = 3),
expand = c(0, 0))
关于r - 如何协调facet_wrap中的轴并缩放="free_y"?,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/52102058/